Intracellular Localization and Trafficking of Fluorescein-Labeled Cisplatin in Human Ovarian Carcinoma Cells
Bibliographic record
Abstract
PURPOSE: We sought to identify the subcellular compartments in which cisplatin [cis-diamminedichloroplatinum (DDP)] accumulates in human ovarian carcinoma cells and define its export pathways. EXPERIMENTAL DESIGN: Deconvoluting digital microscopy was used to identify the subcellular location of fluorescein-labeled DDP (F-DDP) in 2008 ovarian carcinoma cells stained with organelle-specific markers. Drugs that block vesicle movement were used to map the traffic pattern. RESULTS: F-DDP accumulated in vesicles and were not detectable in the cytoplasm. F-DDP accumulated in the Golgi, in vesicles belonging to the secretory export pathway, and in lysosomes but not in early endosomes. F-DDP extensively colocalized with vesicles expressing the copper efflux protein, ATP7A, whose expression modulates the cellular pharmacology of DDP. Inhibition of vesicle trafficking with brefeldin A, wortmannin, or H89 increased the F-DDP content of vesicles associated with the pre-Golgi compartments and blocked the loading of F-DDP into vesicles of the secretory pathway. The importance of the secretory pathway was confirmed by showing that wortmannin and H89 increased whole cell accumulation of native DDP. CONCLUSIONS: F-DDP is extensively sequestered into vesicular structures of the lysosomal, Golgi, and secretory compartments. Much of the distribution to other compartments occurs via vesicle trafficking. F-DDP detection in the vesicles of the secretory pathway is consistent with a major role for this pathway in the efflux of F-DDP and DDP from the cell.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".